"Understanding SQL Server Schema and Querying" matching MCP servers:

A read-only MCP server for PostgreSQL schemas and their git history, enabling AI agents to inspect schema details, migrations, ERDs, missing indexes, circular foreign keys, and churn without write access.

Local MCP tool for understanding JSON Schema files while planning tests, summarizing types, required fields, constraints, and generating placeholder paths without copying data.

Formats SQL queries with support for 14 dialects, keyword casing, and tab width.

Exposes tools that let AI coding agents browse a repo's schema snapshot of tables and columns and validate their SQL against it before running or writing it, so queries referencing invented or stale table and column names get caught and corrected up front. Provides list_tables, describe_table, search_columns, and check_sql over the same snapshot used by the CLI, hook, and CI check.

Validates schema files against customizable lint rules using Claude or Gemini AI, supporting JSON and SQL schemas with rules for naming, structure, and migration safety.

An MCP server that analyzes local or remote GitHub repositories, providing intelligent code context and structure to AI coding assistants.

A MCP server that exposes GraphQL schema information to LLMs like Claude. This server allows an LLM to explore and understand large GraphQL schemas through a set of specialized tools, without needing to load the whole schema into the context

MCP server that integrates sql-sop SQL linter into LLM clients, enabling linting SQL queries and listing lint rules via chat tools.

Scores MCP tool definitions and tool lists from 0-100, flagging vague descriptions, missing parameter docs, non-verb-first naming, oversized enums, and nested schemas with severity, rationale, and concrete fixes. It also validates marketplace listings against platform character caps such as MCPize's 500-character short-description limit before deploy.

Enables offline analysis of MySQL slow query logs, individual SQL statements, and MyBatis mappers to produce deterministic index recommendations and migration SQL without requiring an API key.

Analyzes SQL queries for performance issues, provides optimization suggestions with automated rewriting, and recommends indexes across multiple database dialects (PostgreSQL, MySQL, Oracle, SQL Server).

Provides secure, read-only access to Microsoft SQL Server with multi-layer protection, enabling safe query execution, schema discovery, and SQL script analysis through natural language.

Provides SQL analysis, linting, and dialect conversion using SQLGlot, enabling validation, transpilation, and extraction of table/column references.

Provides tools to prepare and validate ABAP Open SQL statements for SAP's ADT data-preview console, automatically fixing dialect issues like parenthesis spacing and 255-character limits.

An MCP server designed for SQL analysis that demonstrates sampling capabilities by interacting with SQL files in a local directory. It provides a framework for testing client-side sampling while managing SQL-based contexts.

140+ T-SQL static code analysis rules for SQL Database Projects

A metadata-guided, read-only SQL analysis MCP server for DataHub that helps agents perform safe analytical queries using DataHub schema, lineage, ownership, and tags, with a deterministic planner and strict SQL safety layer against local synthetic SQLite, guaranteeing zero write or mutation operations.

Enables interaction with Microsoft SQL Server databases through a virtual filesystem interface, comprehensive stored procedure management with draft-test-deploy workflows, safe write operations with transaction control, and performance analysis capabilities.

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A token-efficient, schema-aware MCP server that enables AI assistants to safely read, modify, query, and validate JSON, YAML, and TOML files with automatic schema detection and format conversion capabilities.